Danielle M. Jorgens
Lawrence Berkeley National Laboratory
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Publication
Featured researches published by Danielle M. Jorgens.
Journal of Cell Biology | 2014
Eliah R. Shamir; Elisa Pappalardo; Danielle M. Jorgens; Kester Coutinho; Wen Ting Tsai; Khaled Aziz; Manfred Auer; Phuoc T. Tran; Joel S. Bader; Andrew J. Ewald
Expression of the transcription factor Twist1 induces dissemination of normal mammary epithelial cells without changing the RNA levels of epithelial-specific genes such as E-cadherin.
Applied and Environmental Microbiology | 2011
Swapnil R. Chhabra; Gareth Butland; Dwayne A. Elias; John-Marc Chandonia; O.-Y. Fok; Tr Juba; A. Gorur; Simon Allen; C. M. Leung; Kimberly L. Keller; Sonia A. Reveco; Grant M. Zane; E. Semkiw; R. Prathapam; B. Gold; Mary E. Singer; M. Ouellet; Evelin Szakal; Danielle M. Jorgens; Morgan N. Price; Witkowska He; Harry R. Beller; Adam P. Arkin; Terry C. Hazen; Mark D. Biggin; Manfred Auer; Judy D. Wall; Jay D. Keasling
ABSTRACT The ability to conduct advanced functional genomic studies of the thousands of sequenced bacteria has been hampered by the lack of available tools for making high-throughput chromosomal manipulations in a systematic manner that can be applied across diverse species. In this work, we highlight the use of synthetic biological tools to assemble custom suicide vectors with reusable and interchangeable DNA “parts” to facilitate chromosomal modification at designated loci. These constructs enable an array of downstream applications, including gene replacement and the creation of gene fusions with affinity purification or localization tags. We employed this approach to engineer chromosomal modifications in a bacterium that has previously proven difficult to manipulate genetically, Desulfovibrio vulgaris Hildenborough, to generate a library of over 700 strains. Furthermore, we demonstrate how these modifications can be used for examining metabolic pathways, protein-protein interactions, and protein localization. The ubiquity of suicide constructs in gene replacement throughout biology suggests that this approach can be applied to engineer a broad range of species for a diverse array of systems biological applications and is amenable to high-throughput implementation.
Journal of Visualized Experiments | 2014
Wen Ting Tsai; Ahmed Hassan; Purbasha Sarkar; Joaquin Correa; Zoltan Metlagel; Danielle M. Jorgens; Manfred Auer
Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation. The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.
PeerJ | 2016
Hidetoshi Mori; Ramray Bhat; Alexandre Bruni-Cardoso; Emily Chen; Danielle M. Jorgens; Kester Coutinho; Katherine Louie; Benjamin Ben Bowen; Jamie L. Inman; Victoria Tecca; Sarah J. Lee; Sabine Becker-Weimann; Trent R. Northen; Motoharu Seiki; Alexander D. Borowsky; Manfred Auer; Mina J. Bissell
Membrane-anchored matrix metalloproteinase 14 (MMP14) is involved broadly in organ development through both its proteolytic and signal-transducing functions. Knockout of Mmp14 (KO) in mice results in a dramatic reduction of body size and wasting followed by premature death, the mechanism of which is poorly understood. Since the mammary gland develops after birth and is thus dependent for its functional progression on systemic and local cues, we chose it as an organ model for understanding why KO mice fail to thrive. A global analysis of the mammary glands’ proteome in the wild type (WT) and KO mice provided insight into an unexpected role of MMP14 in maintaining metabolism and homeostasis. We performed mass spectrometry and quantitative proteomics to determine the protein signatures of mammary glands from 7 to 11 days old WT and KO mice and found that KO rudiments had a significantly higher level of rate-limiting enzymes involved in catabolic pathways. Glycogen and lipid levels in KO rudiments were reduced, and the circulating levels of triglycerides and glucose were lower. Analysis of the ultrastructure of mammary glands imaged by electron microscopy revealed a significant increase in autophagy signatures in KO mice. Finally, Mmp14 silenced mammary epithelial cells displayed enhanced autophagy. Applied to a systemic level, these findings indicate that MMP14 is a crucial regulator of tissue homeostasis. If operative on a systemic level, these findings could explain how Mmp14KO litter fail to thrive due to disorder in metabolism.
Microscopy and Microanalysis | 2010
A. Gorur; C. M. Leung; Danielle M. Jorgens; A. Tauscher; J. P. Remis; David A. Ball; Swapnil R. Chhabra; Veronica Fok; Jil T. Geller; Mary E. Singer; Terry C. Hazen; Tr Juba; Dwayne A. Elias; Judy D. Wall; Mark D. Biggin; Kenneth H. Downing; Manfred Auer
Subcellular localization of proteins in the anaerobic sulfate reducer Desulfovibrio vulgaris via SNAP-tag labeling and photoconversion. A. Gorur,* C.M. Leung,* D. Jorgens,* A. Tauscher,* J.P. Remis,* D.A. Ball,* S. Chhabra,* V. Fok,* J.T. Geller,* M.Singer* T.C. Hazen,* T.Juba,** D. Elias,** J.Wall,**, M. Biggin,* K.H. Downing,* and M. Auer* * Lawrence Berkeley National Laboratory, Berkeley CA 94720 ** University of Missouri, Columbia MO 65211 Systems Biology studies the temporal and spatial 3D distribution of macromolecular complexes with the aim that such knowledge will allow more accurate modeling of biological function and will allow mathematical prediction of cellular behavior. However, in order to accomplish accurate modeling precise knowledge of spatial 3D organization and distribution inside cells is necessary. And while a number of macromolecular complexes may be identified by its 3D structure and molecular characteristics alone, the overwhelming number of proteins will need to be localized using a reporter tag. GFP and its derivatives (XFPs) have been traditionally employed for subcelllar localization using photoconversion approaches, but this approach cannot be taken for obligate anaerobic bacteria, where the intolerance towards oxygen prevents XFP approaches. As part of the GTL-funded PCAP project (now ENIGMA) genetic tools have been developed for the anaerobe sulfate reducer Desulfovibrio vulgaris that allow the high-throughput generation of tagged- protein mutant strains, with a focus on the commercially available SNAP-tag cell system (New England Biolabs, Ipswich, MA), which is based on a modified O6-alkylguanine-DNA alkyltransferase (AGT) tag, that has a dead–end reaction with a modified O6-benzylguanine (BG) derivative and has been shown to function under anaerobic conditions [1]. After initial challenges with respect to variability, robustness and specificity of the labeling signal we have optimized the labeling. Over the last year, as a result of the optimized labeling protocol, we now obtain robust labeling of 20 out of 31 SNAP strains. Labeling for 13 strains were confirmed at least five times. We have also successfully performed photoconversion on 5 of these 13 strains, with distinct labeling patterns for different strains. For example, DsrC robustly localizes to the periplasmic portion of the inner membrane, where as a DNA-binding protein localizes to the center of the cell, where the chromosome is located. Two other proteins – Thiosulfate reductase and ATP binding protein were found to be cytoplasmically distributed, whereas a molybdenum transporter was found to locate to the cell periphery. We judge labeling outcome by 1) SDS gel electrophoresis, followed by direct fluorescence imaging of the gel to address specificity of labeling/confirm expected molecular weight, and subsequent Coomassie analysis to ensure comparable protein levels 2) fluorescence intensity of culture by plate
Microscopy and Microanalysis | 2008
Blake A. Simmons; Dean C. Dibble; Seema Singh; Manfred Auer; Danielle M. Jorgens; Jl Faulon
Archive | 2016
Danielle M. Jorgens; Jamie L. Inman; Michal Wojcik; Claire Robertson; Hildur Palsdottir; Wenting Tsai; Haina Huang; Alexandre Bruni-Cardoso; Claudia S. López; Mina J. Bissell; Ke Xu; Manfred Auer
Development | 2012
Andrew J. Ewald; Robert J. Huebner; Hildur Palsdottir; Jessie K. Lee; Melissa J. Perez; Danielle M. Jorgens; Andrew N. Tauscher; Kevin J. Cheung; Zena Werb; Manfred Auer
Archive | 2009
Bernhard Knierim; Lina Prak; Seema Singh; Danielle M. Jorgens; Marcin Zemla; Kristen M. DeAngelis; Amitha M. Reddy; Jean S. VanderGheynst; Terry C. Hazen; Brad M. Holmes; Rajat Sapra; Blake A. Simmons; Paul D. Adams; Manfred Auer
Archive | 2008
Martin T. Auer; Jonathan Remis; Danielle M. Jorgens; Marcin Zemla; Michael J. Singer; John Schmitt; Yuri A. Gorby; Terry C. Hazen; Jennifer Wall; Dwayne A. Elias; Tamas Torok